Research Engineer, Agentic Systems

Responsibilities

• Design and build end-to-end agentic systems for creative tasks.
• Develop novel approaches for training and adapting the large language models that power these agents.
• Design objectives, datasets, and fine-tuning strategies to improve agent behavior and reliability.
• Explore multimodal reasoning and structured generation for creative control.
• Run systematic experiments to evaluate and improve agent performance in real-world tasks.
• Design evaluation frameworks for agentic workflows in video analysis and editing.
• Analyze failure modes across the full agent loop—including planning, tool use, and execution—and iterate on improvements.

Requirements

• BS, MS, or PhD in Computer Science, Machine Learning, or a related field.
• Strong track record building production ML systems or agentic pipelines.
• Deep understanding of transformers and modern LLM techniques.
• Experience with fine-tuning, alignment, or post-training methods, especially for adapting models to generate structured outputs or drive tool use.
• Comfort owning the full stack, from model-level experiments to deployed agent systems.
• Strong experimental rigor and good judgment about what makes agents work effectively in practice.

Benefits

• Comprehensive medical, dental, and vision plans.
• 401(k) with employer match.
• Commuter benefits.
• Catered lunch multiple days per week.
• Dinner stipend for late work.
• Grubhub subscription.
• Health and wellness perks.
• Multiple team offsites and monthly team events.
• Generous PTO policy.